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Graduate Student Supervision
Doctoral Student Supervision
Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
Capital project development is the mechanism through which mining companies turn promising orebodies into profitable mines. However, broad-scale project success is elusive, with projects frequently exceeding approved cost and schedule estimates. Researchers and mining professionals have pointed to project risk management as a way to improve project success. Despite mature project risk management practices and widespread adoption, projects still repeatedly fail. This is due partly to the current risk management paradigm of prediction and advanced planning, with risks frequently materializing differently than predicted. One method of addressing uncertainty underlying project risks is by embracing flexibility and using an adaptive management approach to risk response. This dissertation demonstrates how adaptive project risk management can preserve project value and reduce time to resolve risks. This dissertation first establishes the state of project risk management practices in mining through an exploratory survey of industry practitioners. The survey fills a literature gap by documenting the methods currently used and attitudes towards them. Next, the adaptive project risk management framework is proposed, describing a structured, iterative process to pursue multiple competing response alternatives in parallel. The framework also details how experimentation, observation, and learning support the adaptive process. A continuous discounted cash flow model and stochastic simulation address uncertain elements of both the risk and the risk response alternatives. The system model provides insight into the effects of different risk responses and the value gained through the adaptive approach. The adaptive framework and system model are explored through two case studies. The first case involved multiple adaptive iterations and demonstrates how the adaptive process gathers and models new information using Bayesian inference while pursuing and dynamically tracking multiple risk response alternatives. The second case study shows how experiments and pilot tests can be used to learn more about the risk and viability of risk responses. These cases demonstrate that an adaptive approach can increase project value, reduce the duration of resolving risks, and potentially limit downside risk compared to a non-adaptive response. The methods proposed in this dissertation give decision-makers the tools to manage project risks more effectively and improve risk management outcomes.
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Mining activities provide comprehensive socio-economic benefits to a nation. There are, however, varying degrees of environmental risks and financial liabilities related to mining. Governments expect mine operators to rehabilitate the environmental condition of disturbed lands once they complete their extraction activities. In the event of insolvency or bankruptcy, regulators also require them to establish that they possess adequate, financial assurance to ensure that mandatory reclamation and closure requirements are performed in accordance with the approved mine closure plans before initiating their mine operations.Such an approved ‘hard’ financial assurance instrument is typically held by the government or in trust by a third-party in escrow until the end of mining and only released when closure and reclamation operations are completed, which in some cases could be decades into the future or sometimes never. Financing these obligations come with a set of other challenges. Requiring a mining company facing both financial difficulties and unsettling market conditions, an epidemic of current times, to take on tens of millions or even hundreds of millions of dollars in ‘hard’ financial liabilities only increases the possibility of its financial collapse and potential reclamation failure.The dissertation focuses on the evaluation of a proposed structured finance mechanism that is expected to offer greater access to required funds from the capital markets and one that aims to assist government regulators with their regulatory compliance, oversight, and enforcement efforts. Even though securitisation has demonstrated the ability to take an illiquid asset or group of such assets, and through financial engineering, transforming it into a marketable financial security for sophisticated investors to invest in, it has yet to be applied to the securitisation of financial assurance requirements. The available financial assurance funding tools and options are also assessed.The dissertation is expected to deepen the discussion surrounding seeking more effective and readily accessible environmental financial assurance instrument solutions for the resource extractive industries. No literature evidence seems to exist to support any earlier study on the prospect of such a financial assurance-backed securitised mechanism. It is therefore of interest to investigate its potential.
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From transportation to infrastructure, from energy to information technology, mining makes a significant contribution to society. It also impacts the lives of millions of people living in regions where mining occurs. Today, an increasing number of individuals and groups have earned a legitimate right to be considered as stakeholders in projects affecting their communities. This has given rise to mining-community conflict and is forcing companies to reconsider the approach to earning and retaining social approval. Global mining leaders have been working to implement policies and practices aligned with corporate social responsibility (CSR) tenets yet conflict between mining companies and the communities that host extractive operations appears to be growing.This research seeks to quantify incidents of mining-community conflict and test a theory that reframing CSR to create shared value could deliver financial returns to mining operations while advancing economic and social conditions in associated communities. It is suggested that the UN 2030 Sustainable Development Goals (SDGs) provide a context for reframing CSR as a strategic business imperative. A new model of engagement is proposed that places the SDGs at the centre of mining-community engagement to align mining with the values of society and rebuild the sector’s current trust deficit.A multi-method research approach is used. The quantitative portion analyzes mining community conflicts from 2012 – 2015 as reported in the international media. Media coverage was hand-coded using a system adapted from conflict literature, and a document analysis of a sub-set of the conflict situations was employed to explore the results. A qualitative, theory-building case study investigates collaboration between personnel at the Cerro Verde Mine and regional stakeholders to address regional water supply issues and develop a strategy with parallel goals: improving operational performance while delivering tangible social benefits. The research seeks to contributes to CSR as a management strategy. The findings confirm there is both monetary and reputational value to investing in core social needs that intersect with business interests. A new model to build trust in mining and advance progress on the SDGs is proposed, and a concept presented that places CSR approaches within life-of-mine stages.
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Mass caving systems require significant capital expenditure and long-term commitment of resources before production commences. Cave mining projects are confronted with numerous challenges in maintaining their construction schedule expectations. Any delay in construction impacts on the production schedule and, in turn, reduces the project value. In order to increase the expected economic value, the construction schedule needs to be accelerated through strategic flexibilities. It is hypothesized that construction acceleration (crashing) can be achieved by prioritizing the construction schedule or changing the construction strategy. This thesis seeks to expand current knowledge on three interrelated domains for decision making in engineering systems—(i) recognition, (ii) modeling and (iii) pricing of flexibility in cave mining construction. An objective of this study was to provide state-of-the-art project formulation techniques employed in planning that can be used to support decision-making processes in cave mining systems. The first domain requires identifying construction strategies that allow the mine management to implement construction crashing in multiple heading development. Three independent and interrelated flexibilities are considered. The second domain requires development of a methodology suitable for investigating and forecasting through modeling the development and construction rates enabling implementation of flexible strategies. A method capable of modeling the development and construction processes with respect to the advance undercut mining strategy is developed, which integrates the geotechnical and equipment-related uncertainties, using the framework of discrete event simulation. Several models are developed to investigate the impact of implementing these flexibilities on the development and construction rates. The results from the flexible models compared to the benchmark models confirmed that significant construction benefits can be achieved. The third domain requires development of an algorithm suitable for evaluating the cost of implementing a construction crashing option that can accommodate delays. A method that is able to respond to schedule uncertainties in construction projects by incorporating the decision-making strategy of project crashing into the budget, including the cost contingency valuation, is developed using the framework of real options and Monte Carlo simulation from a contractor’s perspective. The results indicated that significant change in costs stems from the variation in risk perceptions and confidence levels.
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Master's Student Supervision
Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.
For decades, the mining industry has been identified as one of the top dangerous industries to be employed in. Various efforts have been made to mitigate the safety risk in mining, and even though major improvements have been realized, zero harm has not yet been achieved. As such, many in the industry have shifted from the language and the pursuit of ‘zero-harm’ to focus on the reduction of fatalities and lost-time injuries. While engineering controls and barricading approaches have shown significant contributions to safety performance, researchers have identified the transformation of human behavior as paramount to harm reduction. Training has been identified as a key driver for changing behavior. However, the actual relation between training and injuries is not clear. This gap is addressed in this research. To determine the relationship between training and safety, a surface mine case study was examined. Safety and training data from Letseng Diamonds Mine, Lesotho, which employs 1,804 people to produce 126,000 carats of diamonds a year, is analyzed. A negative correlation is found between the number of injuries incurred and the number of employees who received annual refresher training. This finding confirms the need for safety training and establishes the necessity to train all workers effectively. In essence, results from this sample group and insights obtained from extensive library research on safety and training answer this main research question: Does training surface mine workers improve their safety? In this case, the answer is yes, the higher the number of workers who receive training, the fewer the number of injuries the mine experiences.
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Artisanal and small-scale mining (ASM) is a poverty driven activity in many developing countries, associated with environmental and social degradation such as acid rock drainage, soil erosion, child labour, gambling, prostitution, alcoholism and social instability due to worker migration (Veiga et al., 2014a). Although ASM is an informal and illegal activity, it has been tolerated in developing countries because of its significant economic role in poverty reduction. Indeed, it has been estimated that about 100 million people across developing countries depend on artisanal mining for their livelihoods (World Bank, 2013) and Burkina Faso (located in West Africa) as a developing country is not spared the environment and socio-economic impacts related to ASM.The objectives of the model developed in this study are to mitigate the environmental impacts of artisanal mining while enhancing its socio-economic benefits. The developed model is based on the theory of an economic growth pole (EGP) and its concepts of inter-industry linkage, external economies, and agglomeration. This approach has found success in better and sustainable organization of the agricultural sector in Burkina Faso, where most of the small farmers were previously left alone to produce food without tools, proper regulation, finance and land titles. In this study, the economic and environmental factors affecting artisanal mining have been defined and analysed in order to apply them to the EGP model.The starting EGP model suggests that first a clean processing plant is required to generate sustainable growth, followed by a working organization to centralize activities and ensure better growth distribution for stakeholders (investors, miners, national authorities). As a theoretical approach toward the artisanal mining sector, there are no previous cases of the application of an economic growth pole. Therefore, this study discusses the feasibility of the model and its ability to tackle the impacts of artisanal mining. Importantly, the model tries to tackle the issues in artisanal mining by removing the financial restrictions for implementation of technological services at artisanal mining sites, and by providing a working organization for better distribution of revenues from technological service and for controlling the impacts of processing on the environment and health.
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The world population reached 7.5 billion inhabitants in April 2017. The number of mobile phones will reach 4.77 billion by the end of this year. Mobile phones are made of more than 50 elements. Discoveries of economically viable gold mines in the main producing countries have been slowing down significantly since the 1800s. The global surface temperature of the planet is warming at 0.17⁰C per decade relative to pre-industrial levels. The mobile phone was chosen for this thesis because it is a comprehensive unit of hazardous waste and e-waste. Mobile phones are a municipal solid waste and public health concern. The low energy and low barrier to entry recycling business this thesis envisions recycles precious metals from end of life mobile phones close to where the devices are discarded. This thesis uses system dynamics to model the exponential adoption of mobile phones and its impact in mining and CO₂e emissions. The model is the basis to calculate the return of new precious metal recycling businesses. Climate change is one of the hardest problem men has ever faced because it requires many countries to work together to establish climate centric governance and policies. Businesses are reviewing their supply chain and energy sources. This work focuses on disruptive low energy and low barrier to entry technologies to recycle precious metals from mobile phones. Local recycling businesses will create jobs and stimulate the economy in B.C., Canada, and the world.
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Copper is one of the most important mineral resources. While much unmined copper remains to meet increasing demands, reserve deposit concentrations are dropping while increasing in mineralogical complexity. Porphyry deposits containing the largest reserves have an average grade of 0.25% and often contain elevated concentrations of arsenic in comparison to the deposits that supplied most copper before the 20th century. The current copper porphyry processing scheme first concentrates sulfide ores via froth flotation, then smelts these concentrates. These processes are energy intensive and employ toxic chemical reagents. Low grade deposits must be extensively milled to release ore from gangue. Copper sulfide grains milled to 30 μm in diameter are hard to recover by flotation and an average of 15% of this size fraction is lost to tailings, where it is oxidized, creating acid rock drainage. Copper concentrates containing arsenic at concentrations >2000 ppm cannot be smelted without releasing gaseous arsenic compounds. Common flotation reagents cannot distinguish between arsenic-bearing enargite (Cu₃AsS₄) and chalcopyrite (CuFeS₂). Biotechnology, however, offers a solution to these problems with peptides. Peptides displayed on bacteriophage can be selected for their binding affinity to a specific mineral phase. In this thesis, peptides that bind to chalcopyrite and not to silicate gangue were attached to iron oxide nanoparticles coated with aminopropyl silane via a polyethylene glycol cross-linker. Attachment of the peptides to the nanoparticles was confirmed with FTIR and UV-vis spectroscopy. The nanoparticles were then used to coat and magnetically concentrate chalcopyrite. The nanoparticles preferentially concentrated 38 μm chalcopyrite grains with recoveries near 50%, making them ideally suited to recover the mineral fraction most difficult to float. They were also shown to preferentially coat chalcopyrite over quartz. Concentrates containing 37% chalcopyrite and 13% quartz were collected. Chalcopyrite was concentrated in pure water at pH 7 using non-toxic reagents. Attempts to separate 38 μm enargite and chalcopyrite were met with limited success, though 42% of total copper was recovered from residue otherwise bound for tailings. While this work is still preliminary, these positive results indicate peptide collectors hold great promise. Plans to further explore the potential of peptides are also discussed.
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Resource development projects offer economic opportunities to communities near operations, through the provision of jobs and corporate social responsibility (CSR) initiatives. When the local labour pool is not prepared, or lacks appropriate skills or education avenues for upgrades, labour demands will be filled by a fly-in-fly-out workforce. This system both draws resource benefits away from impacted communities, and incurs high transportation and lodging costs to the company. Improving labour-force quality will require upgrading education resources necessary for acquiring the appropriate post-secondary degrees and certificates for employment in the industry. Before planning education programs, it is important to have an acute understanding of the population’s history, socio-economy, regional education resources, and perspective on local education and employment. This research study examined the Northeastern, British Columbia (NEBC) region, where oil and gas (OAG) development is expected to increase exponentially in the near future with the use of hydraulic fracturing. Due to the specialized skills required for this industry, the local communities are currently ill equipped to participate in the labour boom. An education gap analysis was performed to examines the education disparities and obstacles for varying communities in NEBC. The study used a geographic analysis of regional education opportunities to identify community needs, followed by field work where in-depth interviews and focus groups brought to light local thoughts and perceptions on education, employment and community development. This information can be used by OAG companies to invest in socially responsible programs, that benefit regional communities as they develop the resource.
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Sublevel caving (SLC) is an underground mass mining method where the orebody is divided into a regular network of tunnels. The ore is extracted by level working downwards through the orebody. The caved waste from the overlying rock mass fills the void created by ore extraction generating a dynamic mixing situation between the broken ore and the waste (dilution) from upper levels. The dynamic process of mixing creates a significant challenge in the SLC project to estimate grades reliably. PCSLC is an application developed by Gemcom Software specifically designed for the mine planning of Sub Level Caving projects and operations. It incorporates a rich set of tools to assist with the whole design and planning process including a sophisticated mixing models, it can simulates the material flow observed in caving mines using a technique known as Template Mixing, but due to the complexity that it represents, it is extremely necessary to calibrate its results against real data. The main purpose of this study was to calibrate the mixing model implemented in PCSLC using real data from Newcrest Ridgeway Gold Mine to provide guidelines for SLC project to forecast grade reliably.The methodology used was to collect historical information provided by Ridgeway to reproduce its design and result in PCSLC and then be capable to understand the complexity of gravity flow in SLC. Key information for this purpose was the utilization of the trial marker scale experiments applied at the mine, since it creates the concept of material recovery curve per level. This was fundamental to create a PCSLC model and be able to replicate the tonnage extracted and the grades reported at the mine.One of the main results in this thesis is the understanding of the gravity flow in SLC method and the demonstration of the benefit to use a recovery curve per level as a main driver for mixing modeling. The calibration of the mixing model in PCSLC was successful and the most important part is the guideline created to use in PCSLC to get reliable results in the prediction of grades and dilution for production scheduling purposes.
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The application of geostatistics to strongly skewed data has always been problematic. The ordinary geostatistical methods cannot deal with highly skewed data very well. Multi-Indicator methods are potential candidates for the interpolation of this type of datasets, but the workload associated with them is sometimes intimidating. In this study, six geostatistical estimators, namely, ordinary kriging, simple kriging, universal kriging, trend-only kriging, lognormal kriging and indicator kriging, as well as two deterministic estimating techniques – inverse distance weighted and nearest neighbor – were applied to a highly negatively skewed RQD dataset to determine which one is more appropriate for interpolating a geotechnical model, based on their summary statistics. Universal kriging was identified to be the best method, with the trend being modeled by a quadratic drift item and the residual being estimated with simple kriging. Two simulators – sequential Gaussian and sequential indicator – were applied in this thesis for the purpose of identifying the probabilistic distribution at each location and joint-distribution for multiple locations. A transfer function was defined to transform each of the realizations to a single conceptual cost value for the sake of risk analysis, based on the relation between RQD and tunnel support specifications summarized by Merritt (1972). The distribution of the cost values corresponding to all of the realizations are quasi-normal and no estimators except KT produced a cost value that was less than two standard deviations away from the mean, once again proving the smoothing effect of all linear weighted estimators. If high values account for a dominant percentage in the sample dataset, the estimated RQD models are likely to be over-pessimistic compared with their simulated counterparts. GSLIB was used in this thesis, which in its original form does not impose a limit on the maximum number of samples coming from the same borehole when performing either estimation or simulation. It is recommended to customize the source code of GSLIB to implement this constraint to check what effect it would have on the results, if some commercial FORTRAN compiler can be made handy.
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